The Role of Ventricular–Arterial Coupling in Cardiac Disease and Heart Failure: Assessment, Clinical Implications and Therapeutic Interventions. A Consensus Document of the European Society of Cardiology Working Group on Aorta & Peripheral Vascular Diseases, European Association of Cardiovascular Imaging, and Heart Failure Association
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Ventricular-arterial coupling (VAC) plays a major role in the physiology of cardiac and aortic mechanics, as well as in the pathophysiology of cardiac disease. VAC assessment possesses independent diagnostic and prognostic value and may be used to refine riskstratification and monitor therapeutic interventions. Traditionally, VAC is assessed by the non-invasive measurement of the ratio of arterial (Ea) to ventricular end-systolic elastance (Ees). With disease progression, both Ea and Ees may become abnormal and the Ea/Ees ratio may approximate its normal values. Therefore, the measurement of each component of this ratio or of novel more sensitive markers of myocardial (e.g. global longitudinal strain) and arterial function (e.g. pulse wave velocity) may better characterize VAC. In valvular heart disease, systemic arterial compliance and valvulo-arterial impedance have an established diagnostic and prognostic value and may monitor the effects of valve replacement on vascular and cardiac function. Treatment guided to improve VAC through improvement of both or each one of its components may delay incidence of heart failure and possibly improve prognosis in heart failure. In this consensus document, we describe the pathophysiology, the methods of assessment as well as the clinical implications of VAC in cardiac diseases and heart failure. Finally, we focus on interventions that may improve VAC and thus modify prognosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it